Orientationability analyses of a special class of the Stewart–Gough parallel manipulators using the unit quaternion representation

This paper addresses the orientation-singularity and orientationability analyses of a special class of the Stewart–Gough parallel manipulators whose moving and base platforms are two similar semi-symmetrical hexagons. Employing a unit quaternion to represent the orientation of the moving platform, an analytical expression representing the singularity locus of this class of parallel manipulators in a six-dimensional Cartesian space is obtained. It shows that for a given orientation, the position-singularity locus is a cubic polynomial expression in the moving platform position parameters, and for a given position, the orientation-singularity locus is an analytical expression but not a polynomial directly with respect to the mobile platform orientation parameters. Further inspection shows that for the special class of parallel manipulators, there must exist a nonsingular orientation void in the orientation space around the orientation origin for each position in the position-workspace. Therefore, a new performance index referred to as orientationability is introduced to describe the orientation capability of the special class of manipulators at a given position. A discretization algorithm is proposed for the computation of the orientationability of the special class of manipulators. Moreover, effects of the design parameters and position parameters on the orientationability are investigated in details. Based on the orientationability performance index, another novel performance index referred to as practical orientationability is presented which represents the practical orientation capability of the manipulator at a given position. The practical orientationability not only can satisfy all the kinematic demands and constraints of such class of manipulators, but also can guarantee that the manipulator is nonsingular.     

Learning Structure from Data and Its Application to Ozone Prediction

In this paper we propose an algorithm for structure learning in predictive expert systems based on a probabilistic network representation. The idea is to have the simplest structure (minimum number of links) with acceptable predictive capability. The algorithm starts by building a tree structure based on measuring mutual information between pairs of variables, and then it adds links as necessary to obtain certain predictive performance. We have applied this method for ozone prediction in México City, where the ozone level is used as a global indicator for the air quality in different parts of the city. It is important to predict the ozone level a day, or at least several hours in advance, to reduce the health hazards and industrial losses that occur when the ozone reaches emergency levels. We obtained as a first approximation a tree-structured dependency model for predicting ozone in one part of the city. We observe that even with only three parameters, its estimations are acceptable.A causal network representation and the structure learning techniques produced some very interesting results for the ozone prediction problem. Firstly, we got some insight into the dependence structure of the phenomena. Secondly, we got an indication of which are the important and not so important variables for ozone forecasting. Taking this into account, the measurement and computational costs for ozone prediction could be reduced. And thirdly, we have obtained satisfactory short term ozone predictions based on a small set of the most important parameters.     

液压挖掘机工作装置运动轨迹的智能控制及示教再现

运用模糊智能控制方法对单斗液压挖掘机的动臂和铲土工作装置的运动过程进行跟踪,通过微机的智能化分析学习,实现轨迹控制和示教再现。它对提高单斗液压挖掘机的自控水平和工作效率具有较大意义。文中主要讨论了示教再现原理,系统组成和系统编程。     

Probing the electromagnetic field distribution within a metallic nanodisk

A Co nanolayer is used as a local probe to evaluate the vertical inhomogeneous distribution of the electromagnetic (EM) field within a resonant metallic nanodisk. Taking advantage of the direct relation between the magneto-optical activity and the electromagnetic field intensity in the Co layer, it is shown that the nonuniform EM distribution within the nanodisk under plasmon resonant conditions has maximum values close to the upper and lower flat faces, and a minimum value in the middle.     

Pixel selection for near-infrared chemical imaging (NIR-CI) discrimination between fish and terrestrial animal species in animal protein by-product meals

This paper proposes a method based on near-infrared hyperspectral imaging for discriminating between terrestrial and fish species in animal protein by-products used in livestock feed. Four algorithms (Mahalanobis distance, Kennard-Stone, spatial interpolation, and binning) were compared in order to select an appropriate subset of pixels for further partial least squares discriminant analysis (PLS-DA). The method was applied to a set of 50 terrestrial and 40 fish meals analyzed in the 1000-1700 nm range. Models were then tested using an external validation set comprising 45 samples (25 fish and 20 terrestrial). The PLS-DA models obtained using the four subset-selection algorithms yielded a classification accuracy of 99.80%, 99.79%, 99.85%, and 99.61%, respectively. The results represent a first step for the analysis of mixtures of species and suggest that NIR-CI, providing valuable information on the origin of animal components in processed animal proteins, is a promising method that could be used as part of the EU feed control program aimed at eradicating and preventing bovine spongiform encephalopathy (BSE) and related diseases.     

Theoretical explanation of enhanced low dose rate sensitivity in erbium-doped optical fibers

A new theoretical framework is proposed to explain the dose and dose-rate dependence of radiation-induced absorption in optical fibers. A first-order dispersive kinetics model is used to simulate the growth of the density of color centers during an irradiation. This model succeeds in explaining the enhanced low dose rate sensitivity observed in certain kinds of erbium-doped optical fiber and provides some insight into the physical reasons behind this sensitivity.     

Characterization and Physical Explanation of Energetic Particles on Planck HFI Instrument

The Planck High Frequency Instrument (HFI) has been surveying the sky continuously from the second Lagrangian point (L2) between August 2009 and January 2012. It operates with 52 high impedance bolometers cooled at 100 mK in a range of frequency between 100 GHz and 1 THz with unprecedented sensitivity, but strong coupling with cosmic radiation. At L2, the particle flux is about 5 \(\hbox {cm}^{-2}\,\hbox {s}^{-1}\) and is dominated by protons incident on the spacecraft. Protons with an energy above 40 MeV can penetrate the focal plane unit box causing two different effects: glitches in the raw data from direct interaction of cosmic rays with detectors (producing a data loss of about 15 % at the end of the mission) and thermal drifts in the bolometer plate at 100 mK adding non-Gaussian noise at frequencies below 0.1 Hz. The HFI consortium has made strong efforts in order to correct for this effect on the time ordered data and final Planck maps. This work intends to give a view of the physical explanation of the glitches observed in the HFI instrument in-flight. To reach this goal, we performed several ground-based experiments using protons and \(\alpha \) particles to test the impact of particles on the HFI spare bolometers with a better control of the environmental conditions with respect to the in-flight data. We have shown that the dominant part of glitches observed in the data comes from the impact of cosmic rays in the silicon die frame supporting the micro-machined bolometric detectors propagating energy mainly by ballistic phonons and by thermal diffusion. The implications of these results for future satellite missions will be discussed.     

Sparsity and persistence: mixed norms provide simple signal models with dependent coefficients

Sparse regression often uses ℓ _p norm priors (with p < 2). This paper demonstrates that the introduction of mixed-norms in such contexts allows one to go one step beyond in signal models, and promote some different, structured, forms of sparsity. It is shown that the particular case of the ℓ_1,2 and ℓ_2,1 norms leads to new group shrinkage operators. Mixed norm priors are shown to be particularly efficient in a generalized basis pursuit denoising approach, and are also used in a context of morphological component analysis. A suitable version of the Block Coordinate Relaxation algorithm is derived for the latter. The group-shrinkage operators are then modified to overcome some limitations of the mixed-norms. The proposed group shrinkage operators are tested on simulated signals in specific situations, to illustrate and compare their different behaviors. Results on real data are also used to illustrate the relevance of the approach.     

A Design-Based Structural Test Method for a Switched-Resistor DAC

In this paper, a design-based structural testing method is presented to enable a fast, low cost test for a switched-resistor digital-to-analogue converter (DAC). A 24-bit stereo DAC is used to demonstrate this. After schematic-level simulations and experimental verification, it is found that the dynamic parameter THD can be predicted by the static test. Practical production wafer test and final test results evaluate this structural test method by comparing it with the traditional THD test method. In this paper the simulation results, the relevant measurement results, and the testing results are discussed. Finally, the application recommendations are given.

Evaluation of system codes for analyzing naturally circulating gas loop

Steady-state natural circulation data obtained in a 7 m-tall experimental loop with carbon dioxide and nitrogen are presented in this paper. The loop was originally designed to encompass operating range of a prototype gas-cooled fast reactor passive decay heat removal system, but the results and conclusions are applicable to any natural circulation loop operating in regimes having buoyancy and acceleration parameters within the ranges validated in this loop. Natural circulation steady-state data are compared to numerical predictions by two system analysis codes: GAMMA and RELAP5-3D. GAMMA is a computational tool for predicting various transients which can potentially occur in a gas-cooled reactor. The code has a capability of analyzing multi-dimensional multi-component mixtures and includes models for friction, heat transfer, chemical reaction, and multi-component molecular diffusion. Natural circulation data with two gases show that the loop operates in the deteriorated turbulent heat transfer (DTHT) regime which exhibits substantially reduced heat transfer coefficients compared to the forced turbulent flow. The GAMMA code with an original heat transfer package predicted conservative results in terms of peak wall temperature. However, the estimated peak location did not successfully match the data. Even though GAMMA's original heat transfer package included mixed-convection regime, which is a part of the DTHT regime, the results showed that the original heat transfer package could not reproduce the data with sufficient accuracy. After implementing a recently developed correlation and corresponding heat transfer regime map into GAMMA to cover the whole range of the DTHT regime, we obtained better agreement with the data. RELAP5-3D results are discussed in parallel.